industry news
Subscribe Now

STMicroelectronics and Schneider Electric Reveal Advanced People-Counting Solution using Artificial Intelligence on STM32 Microcontroller

Artificial Intelligence at the very edge enables digital attendance monitoring for smart buildings

Geneva, November 16, 2020 – STMicroelectronics (NYSE: STM), a global semiconductor leader serving customers across the spectrum of electronics applications, and Schneider Electric, the leader in the digital transformation of energy management and automation, are demonstrating a prototype IoT sensor that enables new building-management services and efficiency gains by understanding building-occupancy levels and usage.

The two companies have collaborated to integrate Artificial Intelligence (AI) into a high-performance people-counting sensor, which overcomes the challenge of monitoring attendance in large spaces with multiple entrance points. Schneider Electric will demonstrate this IoT sensor as a guest at ST Live Days, during the IoT&5G session on November 19, 2020.

With the digitization of building occupancy, Schneider is following its mission to be its customers’ digital partner for sustainability and efficiency by delivering new and highly valuable insights such as queue monitoring to assist smart building management while respecting individuals’ privacy by design. The advanced IoT sensor has been developed by combining the high expertise of ST’s AI group and the deep sensor-application expertise of Schneider Electric to identify and embed a high-performing object-detection neural network in a small microcontroller (MCU).

Schneider Electric’s increase in design productivity comes from its use of the STM32Cube.AI toolchain, which has mature capabilities for developing AI applications for the broad portfolio of STM32 MCUs. This allowed Schneider Electric to gain valuable flexibility and efficiency in hardware design from the engineering resources, sophistication, and ease of use provided by the STM32Cube software-development ecosystem.

The prototype people-counting sensor combines a LYNRED ThermEyeTM family thermal imager, integrated in a unique ultra-low-power design created by Schneider Electric, with a Yolo-based Neural Network model running on the recently introduced high-performance STM32H723 MCU from ST.

This promising technology opens a new solution for attendance monitoring and people counting in numerous applications such as monitoring queues, building usage, and social distancing,” said Maxime Loidreau, IoT Sensors Program Manager at Schneider Electric. “Our innovative demonstration, created with STMicroelectronics, finds applications in various segments, from hotels to offices and retail, and more generally any building where knowing attendance and space occupation has a valueThis will redefine the building of the future!

This project demonstrates the power of deep learning to enhance embedded data-processing performance, showing how high-value applications can be hosted on a cost-effective microcontroller-based platform,” added Miguel Castro, AI Solutions Business Line Manager at STMicroelectronics. “Our STM32Cube.AI ecosystem empowers users to create flexible solutions within a fast time-to-market window. Customers can enjoy even greater productivity leveraging the support of our technical team to overcome engineering challenges. 

Further Technical Information

The STM32 AI ecosystem provides essential building blocks for neural networks to run on STM32 MCUs, enabling a cost-effective and power-efficient solution. Various deep-learning frameworks such as Keras, TensorFlow™ Lite, and ONNX exchange format are supported natively.

Included in the ecosystem is the X-CUBE-AI software expansion package, which extends the capabilities of the STM32CubeMX initialization tool to automatically convert pre-trained neural networks, generate optimized libraries for the target MCU, and integrate these into the user’s project. Additional support to automate laborious development tasks includes several ways of validating neural network models and measuring performance on STM32 MCUs without creating the necessary C code by hand.

The general DNN approach supported by ST’s software-development ecosystem, mapped onto the rich STM32 portfolio, lets users efficiently replicate development effort to create products for multiple markets. The STM32H723 MCU powering the demonstration at ST Live Days has excellent credentials for hosting AI applications, including high core performance, up to 1Mbyte Flash, high-speed off-chip memory interfaces, and integrated features for connecting a wide variety of sensor types.

For more information on STM32Cube.AI please go to www.st.com/STM32CubeAI

To see how you can run edge AI applications on STM32 microcontrollers and application processors contact us at edge.ai@st.com

For more information on STM32H7 MCUs please go to https://www.st.com/en/microcontrollers-microprocessors/stm32h7-series.html

About STMicroelectronics

At ST, we are 46,000 creators and makers of semiconductor technologies mastering the semiconductor supply chain with state-of-the-art manufacturing facilities. An independent device manufacturer, we work with our 100,000 customers and thousands of partners to design and build products, solutions, and ecosystems that address their challenges and opportunities, and the need to support a more sustainable world. Our technologies enable smarter mobility, more efficient power and energy management, and the wide-scale deployment of the Internet of Things and 5G technology. Further information can be found at www.st.com.

Leave a Reply

featured blogs
Nov 24, 2020
The ICADVM20.1 and IC6.1.8 ISR15 production releases are now available for download at Cadence Downloads . For information on supported platforms and other release compatibility information, see the... [[ Click on the title to access the full blog on the Cadence Community si...
Nov 23, 2020
It'€™s been a long time since I performed Karnaugh map minimizations by hand. As a result, on my first pass, I missed a couple of obvious optimizations....
Nov 23, 2020
Readers of the Samtec blog know we are always talking about next-gen speed. Current channels rates are running at 56 Gbps PAM4. However, system designers are starting to look at 112 Gbps PAM4 data rates. Intuition would say that bleeding edge data rates like 112 Gbps PAM4 onl...
Nov 20, 2020
[From the last episode: We looked at neuromorphic machine learning, which is intended to act more like the brain does.] Our last topic to cover on learning (ML) is about training. We talked about supervised learning, which means we'€™re training a model based on a bunch of ...

featured video

Improve SoC-Level Verification Efficiency by Up to 10X

Sponsored by Cadence Design Systems

Chip-level testbench creation, multi-IP and CPU traffic generation, performance bottleneck identification, and data and cache-coherency verification all lack automation. The effort required to complete these tasks is error prone and time consuming. Discover how the Cadence® System VIP tool suite works seamlessly with its simulation, emulation, and prototyping engines to automate chip-level verification and improve efficiency by ten times over existing manual processes.

Click here for more information about System VIP

featured paper

Top 9 design questions about digital isolators

Sponsored by Texas Instruments

Looking for more information about digital isolators? We’re here to help. Based on TI E2E™ support forum feedback, we compiled a list of the most frequently asked questions about digital isolator design challenges. This article covers questions such as, “What is the logic state of a digital isolator with no input signal?”, and “Can you leave unused channel pins on a digital isolator floating?”

Click here to download the whitepaper

Featured Chalk Talk

Introducing Google Coral

Sponsored by Mouser Electronics and Google

AI inference at the edge is exploding right now. Numerous designs that can’t use cloud processing for AI tasks need high-performance, low-power AI acceleration right in their embedded designs. Wouldn’t it be cool if those designs could have their own little Google TPU? In this episode of Chalk Talk, Amelia Dalton chats with James McKurkin of Google about the Google Coral edge TPU.

More information about Coral System on Module